Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
about
Diabetes technology: markers, monitoring, assessment, and control of blood glucose fluctuations in diabetes.Predicting subcutaneous glucose concentration using a latent-variable-based statistical method for type 1 diabetes mellitus"Smart" continuous glucose monitoring sensors: on-line signal processing issues.Diabetes: Models, Signals, and Control.Italian contributions to the development of continuous glucose monitoring sensors for diabetes management.How Much Is Short-Term Glucose Prediction in Type 1 Diabetes Improved by Adding Insulin Delivery and Meal Content Information to CGM Data? A Proof-of-Concept StudyReal-time glucose estimation algorithm for continuous glucose monitoring using autoregressive models.Multiple-Input Subject-Specific Modeling of Plasma Glucose Concentration for Feedforward Control.Personalized State-space Modeling of Glucose Dynamics for Type 1 Diabetes Using Continuously Monitored Glucose, Insulin Dose, and Meal Intake: An Extended Kalman Filter Approach.Real-time improvement of continuous glucose monitoring accuracy: the smart sensor conceptA novel adaptive-weighted-average framework for blood glucose prediction.Experimental evaluation of a recursive model identification technique for type 1 diabetes.An early warning system for hypoglycemic/hyperglycemic events based on fusion of adaptive prediction models.Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.Effect of concurrent oxygen therapy on accuracy of forecasting imminent postoperative desaturation.Continuous glucose monitoring: real-time algorithms for calibration, filtering, and alarms.Chaotic time series prediction for glucose dynamics in type 1 diabetes mellitus using regime-switching models.Evaluation of short-term predictors of glucose concentration in type 1 diabetes combining feature ranking with regression models.Mathematical modeling research to support the development of automated insulin-delivery systemsUpdate on mathematical modeling research to support the development of automated insulin delivery systems.Signal processing algorithms implementing the "smart sensor" concept to improve continuous glucose monitoring in diabetes.Stochastic Seasonal Models for Glucose Prediction in the Artificial Pancreas.A simplification of Cobelli's glucose-insulin model for type 1 diabetes mellitus and its FPGA implementation.Self-Powered Implantable Skin-Like Glucometer for Real-Time Detection of Blood Glucose Level In Vivo
P2860
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P2860
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
description
2008 nî lūn-bûn
@nan
2008 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
@ast
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
@en
type
label
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
@ast
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
@en
prefLabel
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
@ast
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
@en
P2093
P1476
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
@en
P2093
Adiwinata Gani
Andrei V Gribok
Jaques Reifman
Srinivasan Rajaraman
W Kenneth Ward
P304
P356
10.1109/TBME.2008.2005937
P577
2008-09-16T00:00:00Z